Digitizing mortality is more than building tools. It is an end-to-end, interoperable infrastructure that supports digital medical certification, ICD-11 coding, automated underlying-cause of death selection, quality assurance, data analysis, and open participation so countries can produce comparable, timely mortality data for policy and action.
To reduce delays, improve comparability, and make cause-of-death processing auditable and explainable.
Standards, rules, and digital public goods co-developed with countries and partners. For the people by the people.
Governance, capacity building, integration, and sustainability enable scale.
A single, coherent flow: capture → code → select → analyse → improve. Each component is designed to be transparent, reproducible, and interoperable.
Medical certification of cause of death (eMCCD data fields) and verbal autopsy structured capture.
Convert text to standardized ICD-11 codes (multilingual, smart search, postcoordination where relevant).
DORIS applies ICD mortality rules transparently and reproducibly for underlying cause of death selection.
ANACoD analyses mortality data, identifies ill-defined causes, unusual patterns, and data quality gaps for routine improvement.
Open proposals, value sets, rule editing/testing, and guidance updates, evidence-based participation.
Practical components that implement standards and rules. Countries can adopt parts and scale progressively, while keeping interoperability through shared specifications.
Multilingual smart coding with support for retaining clinical detail (including postcoordination where relevant), enabling consistent downstream processing.
Applies ICD mortality rules transparently and reproducibly, with detailed steps applied so users can explain how the selection was made.
Provides a systematic, automated analysis of mortality and cause-of-death data to identify quality gaps, support routine review, and guide evidence-based improvement
Supports coding quality evaluation and provides warnings, helping strengthen consistency and training outcomes.
Maintain standards and rules openly. Participation is evidence-based: contributors propose improvements, test cases, and help maintain shared value sets and mappings.
Data quality starts before the first code. Standardized capture and training reduce “garbage in, garbage out” and enable reliable analysis.
Guidance and learning resources to support accurate medical certification practices and strengthen the quality of input data.
Defines data fields and encoding so medical certificates of cause of death can be processed consistently across national systems and tools.
Structured data capture for deaths outside facilities, aligned to enable consistent processing and analysis.
Rule clarifications, value sets updates, and guidance improvements are maintained openly with countries and partners. Outputs remain explainable and auditable over time.
Propose updates to selection rules, value sets, and guidance using evidence and clear rationale. Test changes and support shared maintenance.
Ensure stakeholders can trace how text becomes codes, and how codes become an underlying cause of death critical for trust in mortality statistics.
Digitization succeeds when governance, integration, and capacity building are planned alongside tooling. Partners can support deployment and scale.